High dynamic range processing for magnetic resonance imaging

Utility of multiparametric pre-operative magnetic resonance imaging in differentiation of chordoid meningioma from the other histopathological subtypes of meningioma-a retrospective study

PURPOSE

To determine the magnetic resonance imaging (MRI) features which could pre-operatively differentiate chordoid meningioma (CM) from other histopathological subtypes of meningioma.

METHODS

Retrospective analysis of pre-operative MRI of cases with histopathologically confirmed diagnosis of meningioma during the last 5 years at our institute was done. T1W, T2W, FLAIR sequences, and post-contrast enhancement were evaluated on a qualitative scale. Normalized ADC ratios (nADCR) and normalized fractional anisotropy ratios (nFAR) were derived. The intratumoral susceptibility score (ITSS), presence of sunburst pattern of vasculature, bone changes, tumour-parenchyma interface, and oedema-to-tumour ratio were also determined.

RESULTS

A total of 81 lesions were analyzed out of which 15 were CM. CM showed a higher relative contrast enhancement as compared to all other subtypes except for angiomatous and microcystic meningioma. Relative signal intensity on FLAIR could differentiate CM from transitional meningioma. nFAR was found to be significantly higher in fibroblastic meningioma and significantly lower in microcystic meningiomas as compared to CM. Anaplastic meningiomas were remarkable for bone changes and an ill-defined tumour-brain interface in significantly higher proportion of cases as compared to CM. nADCR > 1.5 was found to be an independent predictor of CM with a sensitivity of 84.6%, specificity of 89.8%, positive predictive value of 64.7%, and negative predictive value of 96.4%.

CONCLUSION

Routine pre-operative MRI may be able to differentiate CM from other meningioma subtypes and a cut-off value of greater than 1.5 for nADCR could be predictive of > 50% chordoid histology of meningioma with a high sensitivity, specificity, and negative predictive value.

High dynamic range ultrasound imaging

PURPOSE

High dynamic range (HDR) imaging is a popular computational photography technique that has found its way into every modern smartphone and camera. In HDR imaging, images acquired at different exposures are combined to increase the luminance range of the final image, thereby extending the limited dynamic range of the camera. Ultrasound imaging suffers from limited dynamic range as well; at higher power levels, the hyperechogenic tissue is overexposed, whereas at lower power levels, hypoechogenic tissue details are not visible. In this work, we apply HDR techniques to ultrasound imaging, where we combine ultrasound images acquired at different power levels to improve the level of detail visible in the final image.

METHODS

Ultrasound images of ex vivo and in vivo tissue are acquired at different acoustic power levels and then combined to generate HDR ultrasound (HDR-US) images. The performance of five tone mapping operators is quantitatively evaluated using a similarity metric to determine the most suitable mapping for HDR-US imaging.

RESULTS

The ex vivo and in vivo results demonstrated that HDR-US imaging enables visualizing both hyper- and hypoechogenic tissue at once in a single image. The Durand tone mapping operator preserved the most amount of detail across the dynamic range.

CONCLUSIONS

Our results strongly suggest that HDR-US imaging can improve the utility of ultrasound in image-based diagnosis and procedure guidance.